Advanced computing environments are rapidly adopting AI to accelerate, automate analysis, and streamline decision-making. That speed is useful, but it introduces a problem IT teams and research leaders often underestimate: synthetic confidence. As AI-generated outputs begin to look authoritative, organizations risk accepting flawed results, weak explanations, or manipulated content with less scrutiny than they would apply to a human analyst. This session explores how trust is formed, misplaced, and exploited in AI-enabled computing environments, particularly where high-performance computing, sensitive research, and collaborative workflows intersect. Attendees ill walk away with a practical framework for improving verification culture, reducing automation bias, and building security controls that protect not just systems, but judgment itself.
